Methods – Page 5 – Integration and Implementation Insights

Modeling as empowerment

August 24, 2022April 21, 2016

By Laura Schmitt Olabisi

Who can make systems change? The challenges of complexity are intensely felt by those who are trying to make strategic interventions in coupled human-environmental systems in order to fulfill personal, societal, or institutional goals. The activists, leaders, and decision-makers I work with often feel overwhelmed by trying to deal with multiple problems at once, with limited time, resources, and attention. We need tools to help leaders cut through the complexity so that they can identify the most effective strategies to make change.

This is where participatory system dynamics modelers like myself come in.

La modélisation participative, un lieu privilégié pour l’interdisciplinarité? / Participatory modeling: An ideal place for interdisciplinarity?

August 24, 2022April 7, 2016

By Pierre Bommel

An English version of this post is available

La modélisation participative cherche à impliquer un groupe de personnes dans la conception et la révision d’un modèle. L’objectif à terme consiste à mieux caractériser les problèmes actuels et imaginer collectivement comment tenter de les résoudre. Dans le domaine de l’environnement en particulier, il apparaît nécessaire que les acteurs concernés se sentent impliqués dans la démarche de modélisation, afin qu’ils puissent exprimer leurs propres points de vue, mais aussi pour mieux s’engager dans des décisions collectives. De ce fait, pour aborder la gestion intégrée des ressources, il est nécessaire de mettre les acteurs au centre des préoccupations de recherche, à la fois lors de la phase la conception du modèle mais aussi pour l’exploration de ces scénarios.

Can mapping mental models improve research implementation?

August 17, 2020January 27, 2016

By Katrin Prager

We all have different mental models of the environment and the people around us. They help us make sense of what we experience. In a recent project exploring how to improve soil management (PDF 250KB), Michiel Curfs and I used data collected from Spanish farmers and our own experience to develop and compare the mental model of a typical Spanish farmer growing olives with that of a hypothetical scientist. How did their mental models of soil degradation differ? Mainly in terms of understanding the role of ploughing, and the importance of drivers for certain soil management activities. There were only a few areas of overlap: both scientist and farmer were concerned about fire risk and acknowledged weeds. We emphasise the importance of two-way communication, and recommend starting by focusing on areas of overlap and then moving to areas that are different. Without integrating understandings from both mental models, the scientist will carry on making recommendations for reducing soil degradation that the farmer cannot implement or does not find relevant.

The promise of using similar methods across disciplines

September 13, 2021January 13, 2016

By Allison Metz

Interdisciplinarity has the potential to broaden and deepen our understanding and application of methods and tools to address complex challenges. When we embrace interdisciplinarity we broaden what we know about the potential methods for assessing and tackling problems, and we deepen our understanding of specific methods by applying these methods across different contexts. In my pursuit to understand co-creative processes by interconnected stakeholders – i.e., the deep and authentic engagement of stakeholders across governance, science, and community boundaries to identify and optimize the use of evidence for positive outcomes – I have been influenced by methods used outside of my discipline of implementation science and current context of child welfare services. For example, I recently read an article that studied the co-production of knowledge in soils governance (Prager & McKee, 2015) in the United Kingdom and was struck by the usefulness of these ideas for child welfare services in the United States.

Modelling is the language of scientific discovery

September 23, 2021December 2, 2015

By Steven Gray

Modeling is the language of scientific discovery and has significant implications for how scientists communicate within and across disciplines. Whether modeling the social interactions of individuals within a community in anthropology, the trade-offs of foraging behaviors in ecology, or the influence of warming ocean temperatures on circulation patterns in oceanography, the ability to represent empirical or theoretical understanding through modeling provides scientists with a semi-standardized language to explain how we think the world works. In fact, modeling is such a basic part of human reasoning and communication that the formal practice of scientific modeling has been recently extended to include non-scientists, especially as a way to understand complex and poorly understood socio-environmental dynamics and to improve collaborative research.